Human interactive proofs (HIPs), also sometimes referred to as “CAPTCHAs” (Completely Automated Public Turing test to tell Computers and Humans Apart), are widely used on the Worldwide Web (WWW) for distinguishing actual human users from computer programs, bots, and the like. (Bots are generally software programs, scripts, or the like, that run repetitive automated tasks on the Internet.) For example, HIPs are often used by online email providers to prevent spammers from employing automated bots to sign up for a large number of free email accounts to use for sending spam. HIPs are also commonly used to prevent bot use and abuse of various other online services, such as online voting, purchasing of event tickets, or accessing certain databases, websites, blogs, forums, and the like.
HIPs can be text-based or non-text-based. Most of the HIPs currently in widespread use are text-based HIPs that utilize distorted and overlapping text characters. However, optical character recognition and character segmentation technologies have advanced sufficiently to enable circumvention of many conventional text-based HIPs. Additionally, many humans already find these text-based HIPs difficult to read, and thus, attempting to increase the security of these text-based HIPs by making them more difficult for a computer program to read also may make them unreadable for many humans. Further, most non-text-based HIPs are not practical for large-scale applications, which may need to produce millions of HIP tests on a daily basis. In addition, many non-text-based HIPs allow bots to achieve too high a success rate, such as by random guessing, and therefore are not sufficiently effective. For example, even if an HIP limits a bot's success rate to as low as 1%, this is generally not sufficient to prevent a spammer from acquiring a large number of spam email accounts because the cost of each attempt is very small.